Overall Statistics
Total Orders
99
Average Win
14.20%
Average Loss
-9.13%
Compounding Annual Return
-4.454%
Drawdown
81.000%
Expectancy
-0.024
Start Equity
100000
End Equity
32097.42
Net Profit
-67.903%
Sharpe Ratio
-0.287
Sortino Ratio
-0.316
Probabilistic Sharpe Ratio
0.000%
Loss Rate
62%
Win Rate
38%
Profit-Loss Ratio
1.56
Alpha
-0.039
Beta
-0.081
Annual Standard Deviation
0.148
Annual Variance
0.022
Information Ratio
-0.382
Tracking Error
0.226
Treynor Ratio
0.526
Total Fees
$77.61
Estimated Strategy Capacity
$1200000.00
Lowest Capacity Asset
EWM R735QTJ8XC9X
Portfolio Turnover
0.43%
# https://quantpedia.com/strategies/mean-reversion-effect-in-country-equity-indexes/
#
# The investment universe consists of 16 ETFs (funds) that invest in individual countries’ equity indexes. Go long on the 
# bottom four countries with the worst 36 – month return and go short on the top 4 countries with the best 36-month return. Rebalance every three years.

from AlgorithmImports import *

class ReversalEffectinInternationalEquityETFs(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2000, 1, 1)  
        self.SetCash(100000) 

        # Daily ROC data.
        self.perf = {}

        self.period = 36 * 21
        self.SetWarmUp(self.period)
        
        self.symbols = [
                        "EWA",  # iShares MSCI Australia Index ETF
                        "EWO",  # iShares MSCI Austria Investable Mkt Index ETF
                        "EWK",  # iShares MSCI Belgium Investable Market Index ETF
                        "EWZ",  # iShares MSCI Brazil Index ETF
                        "EWC",  # iShares MSCI Canada Index ETF
                        "FXI",  # iShares China Large-Cap ETF
                        "EWQ",  # iShares MSCI France Index ETF
                        "EWG",  # iShares MSCI Germany ETF 
                        "EWH",  # iShares MSCI Hong Kong Index ETF
                        "EWI",  # iShares MSCI Italy Index ETF
                        "EWJ",  # iShares MSCI Japan Index ETF
                        "EWM",  # iShares MSCI Malaysia Index ETF
                        "EWW",  # iShares MSCI Mexico Inv. Mt. Idx
                        "EWN",  # iShares MSCI Netherlands Index ETF
                        "EWS",  # iShares MSCI Singapore Index ETF
                        "EZA",  # iShares MSCI South Africe Index ETF
                        "EWY",  # iShares MSCI South Korea ETF
                        "EWP",  # iShares MSCI Spain Index ETF
                        "EWD",  # iShares MSCI Sweden Index ETF
                        "EWL",  # iShares MSCI Switzerland Index ETF
                        "EWT",  # iShares MSCI Taiwan Index ETF
                        "THD",  # iShares MSCI Thailand Index ETF
                        "EWU",  # iShares MSCI United Kingdom Index ETF
                        "SPY",  # SPDR S&P 500 ETF
                        ]

        for symbol in self.symbols:
            data = self.AddEquity(symbol, Resolution.Daily)
            data.SetFeeModel(CustomFeeModel())
            data.SetLeverage(15)
            
            self.perf[symbol] = self.ROC(symbol, self.period, Resolution.Daily)
        
        # rebalance month
        self.month = 36
        self.recent_month = -1

    def OnData(self, data):
        if self.IsWarmingUp:
            return
        
        if self.Time.month == self.recent_month:
            return
        self.recent_month = self.Time.month
        
        self.month += 1
        if self.month > 36:
           self.month = 1
        else:
            return
           
        sorted_by_momentum = sorted([x for x in self.perf.items() if x[1].IsReady and x[0] in data and data[x[0]]], key = lambda x: x[1].Current.Value, reverse = True)
        long = [x[0] for x in sorted_by_momentum[-4:]]
        short = [x[0] for x in sorted_by_momentum[:4]]
        
        # trade execution
        invested = [x.Key.Value for x in self.Portfolio if x.Value.Invested]
        for symbol in invested:
            if symbol not in long + short:
                self.Liquidate(symbol)
        
        for symbol in long:
            self.SetHoldings(symbol, 1 / len(long))
        for symbol in short:
            self.SetHoldings(symbol, -1 / len(short))

# Custom fee model
class CustomFeeModel(FeeModel):
    def GetOrderFee(self, parameters):
        fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
        return OrderFee(CashAmount(fee, "USD"))